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SANE: Semantic-Aware Namespacein Ultra-Large-Scale File
Systems
The explosive growth in data volume and complexity imposes great challenges for file systems.
To address these challenges, an innovative namespace management scheme is in desperate need
to provide both the ease and efficiency of data access. In almost all today's file systems, the
namespace management is based on hierarchical directory trees. This tree-based namespace
scheme is prone to severe performance bottlenecks and often fails to provide real-time response
to complex data lookups. This paper proposes a Semantic-Aware Namespace scheme, called
SANE, which provides dynamic and adaptive namespace management for ultra- large storage
systems with billions of files. SANE introduces a new naming methodology based on the notion
of semantic-aware per- file namespace, which exploits semantic correlations among files, to
dynamically aggregate correlated files into small, flat but readily manageable groups to achieve
fast and accurate lookups. SANE is implemented as a middleware in conventional file systems
and works orthogonally with hierarchical directory trees. The semantic correlations and file
groups identified in SANE can also be used to facilitate file prefetching and data de-duplication,
among other system- level optimizations. Extensive trace-driven experiments on
our PROTOTYPE implementation validate the efficacy and efficiency of SANE.

2. Existing System
The explosive growth in data volume and complexity imposes great challenges for file systems.
To address these challenges, an innovative namespace management scheme is in desperate need
to provide both the ease and efficiency of data access. In almost all today's file systems, the
namespace management is based on hierarchical directory trees. This tree-based namespace
scheme is prone to severe performance bottlenecks and often fails to provide real-time response
to complex data lookups.
Proposed System
This paper proposes a Semantic-Aware Namespace scheme, called SANE, which provides
dynamic and adaptive namespace management for ultra- large storage systems with billions of
files. SANE introduces a new naming methodology based on the notion of semantic-aware per-file
namespace, which exploits semantic correlations among files, to dynamically aggregate
correlated files into small, flat but readily manageable groups to achieve fast and accurate
lookups. SANE is implemented as a middleware in conventional file systems and works
orthogonally with hierarchical directory trees. The semantic correlations and file groups
identified in SANE can also be used to facilitate file prefetching and data de-duplication, among
other system- level optimizations. Extensive trace-driven experiments on our PROTOTYPE
implementation validate the efficacy and efficiency of SANE.
System Specification
Hardware Requirements:
• System : Pentium IV 2.4 GHz.
• Hard Disk : 40 GB.
• Floppy Drive : 1.44 Mb.

3. • Monitor : 14’ Colour Monitor.
• Mouse : Optical Mouse.
• Ram : 512 Mb.
Software Requirements:
• Operating system : Windows 7.
• Coding Language : ASP.Net with C#
• Data Base : SQL Server 2008.